YiLi225

import math
def mySqrt(x):
    if type(x) not in [int, float] or x < 0:
        raise ExceptionGroup("twice", 
                             [ValueError(999),
                              TypeError("Work with Numbers Only")])
    else:
      return math.sqrt(x)

print(mySqrt('-10'))

YiLi225

## With asyncio.TaskGroup
async def run_errands():
    async with asyncio.TaskGroup() as tg:
        for errand, (start_time, time_to_finish) in errandsDict.items():
            tg.create_task(errands_log(errand, 
                                       start_time, 
                                       time_to_finish))

YiLi225

(base) C:\Desktop>python async.py
(Pick Up Kids) starting at 6am
(Pick Up Kids) done at 7am
======;
(Return Packages) starting at 9am
(Return Packages) done at 10am
======;
(Grocery Shopping) starting at 11am
(Grocery Shopping) done at 13am
======;

YiLi225

from typing import Any, Type, TypeVar
from dataclasses import dataclass

curType = TypeVar('curType', bound='Rectangle')

class Rectangle:
    def __init__(self, length: float) -> None:
        self.length = length

    @classmethod

YiLi225

from bs4 import BeautifulSoup
from urllib.request import urlopen, Request
from collections import defaultdict
tagInfo = defaultdict(list)

for tag in tags:
    startLink = "https://medium.com/tag/"+tag
    
    response = requests.get(startLink, allow_redirects=True)
    page = response.content

YiLi225

--- However, COALESCE() NOT WORK for Empty or NA string, instead, use CASE WHEN
SELECT 
  ID_VAR, 
  EMPTY_STR_VAR, 
  COALESCE(EMPTY_STR_VAR, 'MISSING') AS COALESCE_EMPTY_STR_VAR, 
  CASE WHEN EMPTY_STR_VAR = ' ' THEN 'EMPTY_MISSING' END AS CASEWHEN_EMPTY_STR_VAR, 
  
  NA_STR_VAR, 
  CASE WHEN NA_STR_VAR = 'NA' THEN 'NA_MISSING' END AS CASEWHEN_NA_STR_VAR
FROM 

YiLi225

### Install: !pip install textstate
import textstat
# curText = doc_set[27310]
# (1) Flesch readability score
print(textstat.flesch_reading_ease(curText))
68.94  ## indicating Standard
# (2) Reading time, assuming 15 ms/character
print(textstat.reading_time(curText, ms_per_char=15))
3.8   ## 3.8s to read 
# (3) Grade level: Intended for text written for children up to grade four

YiLi225

## Install: !pip install -U layer
import layer
df = layer.get_dataset('layer/wikitext/datasets/wikitext-103-train').to_pandas()
doc_set = [i for i in df.sentence.str.lower()]

YiLi225

# Install: !pip install sentence_transformers
from sentence_transformers import SentenceTransformer
model = SentenceTransformer('distilbert-base-nli-mean-tokens')

# sentences = [doc_set[9234], doc_set[9239], doc_set[1131966]]
sentence_embeddings = model.encode(sentences)

# Calculate cosine distance of the embeddings
from scipy.spatial import distance
print(1 - distance.cosine(sentence_embeddings[0], sentence_embeddings[1]))

YiLi225

##### Generate the wordcloud #####
my_freq_grams = freq_grams

curMask = np.array(Image.open(pathToYourPic))
wc = WordCloud(background_color='white',
               stopwords=stopwords,
                      width=800, 
                      height=600, 
                      relative_scaling=.6, 
                      max_font_size=60,